Tables

BinTableHDU

class astropy.io.fits.BinTableHDU(data=None, header=None, name=None, uint=False, ver=None, character_as_bytes=False)

Bases: _TableBaseHDU

Binary table HDU class.

Parameters:

dataarray, FITS_rec, or Table

Data to be used.

headerHeader

Header to be used.

namepython:str

Name to be populated in EXTNAME keyword.

uintbool, optional

Set to True if the table contains unsigned integer columns.

verpython:int > 0 or python:None, optional

The ver of the HDU, will be the value of the keyword EXTVER. If not given or None, it defaults to the value of the EXTVER card of the header or 1. (default: None)

character_as_bytesbool

Whether to return bytes for string columns. By default this is False and (unicode) strings are returned, but this does not respect memory mapping and loads the whole column in memory when accessed.

add_checksum(when=None, override_datasum=False, checksum_keyword='CHECKSUM', datasum_keyword='DATASUM')

Add the CHECKSUM and DATASUM cards to this HDU with the values set to the checksum calculated for the HDU and the data respectively. The addition of the DATASUM card may be overridden.

Parameters:

whenpython:str, optional

comment string for the cards; by default the comments will represent the time when the checksum was calculated

override_datasumbool, optional

add the CHECKSUM card only

checksum_keywordpython:str, optional

The name of the header keyword to store the checksum value in; this is typically ‘CHECKSUM’ per convention, but there exist use cases in which a different keyword should be used

datasum_keywordpython:str, optional

See checksum_keyword

Notes

For testing purposes, first call add_datasum with a when argument, then call add_checksum with a when argument and override_datasum set to True. This will provide consistent comments for both cards and enable the generation of a CHECKSUM card with a consistent value.

add_datasum(when=None, datasum_keyword='DATASUM')

Add the DATASUM card to this HDU with the value set to the checksum calculated for the data.

Parameters:

whenpython:str, optional

Comment string for the card that by default represents the time when the checksum was calculated

datasum_keywordpython:str, optional

The name of the header keyword to store the datasum value in; this is typically ‘DATASUM’ per convention, but there exist use cases in which a different keyword should be used

Returns:

checksumpython:int

The calculated datasum

Notes

For testing purposes, provide a when argument to enable the comment value in the card to remain consistent. This will enable the generation of a CHECKSUM card with a consistent value.

property columns

The ColDefs objects describing the columns in this table.

copy()

Make a copy of the table HDU, both header and data are copied.

dump(datafile=None, cdfile=None, hfile=None, overwrite=False)

Dump the table HDU to a file in ASCII format. The table may be dumped in three separate files, one containing column definitions, one containing header parameters, and one for table data.

Parameters:

datafilepython:path-like object or python:file-like object, optional

Output data file. The default is the root name of the fits file associated with this HDU appended with the extension .txt.

cdfilepython:path-like object or python:file-like object, optional

Output column definitions file. The default is None, no column definitions output is produced.

hfilepython:path-like object or python:file-like object, optional

Output header parameters file. The default is None, no header parameters output is produced.

overwritebool, optional

If True, overwrite the output file if it exists. Raises an OSError if False and the output file exists. Default is False.

Notes

The primary use for the dump method is to allow viewing and editing the table data and parameters in a standard text editor. The load method can be used to create a new table from the three plain text (ASCII) files.

• datafile: Each line of the data file represents one row of table data. The data is output one column at a time in column order. If a column contains an array, each element of the column array in the current row is output before moving on to the next column. Each row ends with a new line.

  Integer data is output right-justified in a 21-character field followed by a blank. Floating point data is output right justified using ‘g’ format in a 21-character field with 15 digits of precision, followed by a blank. String data that does not contain whitespace is output left-justified in a field whose width matches the width specified in the TFORM header parameter for the column, followed by a blank. When the string data contains whitespace characters, the string is enclosed in quotation marks (""). For the last data element in a row, the trailing blank in the field is replaced by a new line character.

  For column data containing variable length arrays (‘P’ format), the array data is preceded by the string 'VLA_Length= ' and the integer length of the array for that row, left-justified in a 21-character field, followed by a blank.

  Note

  This format does not support variable length arrays using the (‘Q’ format) due to difficult to overcome ambiguities. What this means is that this file format cannot support VLA columns in tables stored in files that are over 2 GB in size.

  For column data representing a bit field (‘X’ format), each bit value in the field is output right-justified in a 21-character field as 1 (for true) or 0 (for false).

• cdfile: Each line of the column definitions file provides the definitions for one column in the table. The line is broken up into 8, sixteen-character fields. The first field provides the column name (TTYPEn). The second field provides the column format (TFORMn). The third field provides the display format (TDISPn). The fourth field provides the physical units (TUNITn). The fifth field provides the dimensions for a multidimensional array (TDIMn). The sixth field provides the value that signifies an undefined value (TNULLn). The seventh field provides the scale factor (TSCALn). The eighth field provides the offset value (TZEROn). A field value of "" is used to represent the case where no value is provided.

• hfile: Each line of the header parameters file provides the definition of a single HDU header card as represented by the card image.

filebytes()

Calculates and returns the number of bytes that this HDU will write to a file.

fileinfo()

Returns a dictionary detailing information about the locations of this HDU within any associated file. The values are only valid after a read or write of the associated file with no intervening changes to the HDUList.

Returns:

python:dict or python:None

The dictionary details information about the locations of this HDU within an associated file. Returns None when the HDU is not associated with a file.

Dictionary contents:

Key	Value
file	File object associated with the HDU
filemode	Mode in which the file was opened (readonly, copyonwrite, update, append, ostream)
hdrLoc	Starting byte location of header in file
datLoc	Starting byte location of data block in file
datSpan	Data size including padding

classmethod from_columns(columns, header=None, nrows=0, fill=False, character_as_bytes=False, **kwargs)

Given either a ColDefs object, a sequence of Column objects, or another table HDU or table data (a FITS_rec or multi-field numpy.ndarray or numpy.recarray object, return a new table HDU of the class this method was called on using the column definition from the input.

See also FITS_rec.from_columns.

Parameters:

columnspython:sequence of Column, ColDefs astropy:-like

The columns from which to create the table data, or an object with a column-like structure from which a ColDefs can be instantiated. This includes an existing BinTableHDU or TableHDU, or a numpy.recarray to give some examples.

If these columns have data arrays attached that data may be used in initializing the new table. Otherwise the input columns will be used as a template for a new table with the requested number of rows.

headerHeader

An optional Header object to instantiate the new HDU yet. Header keywords specifically related to defining the table structure (such as the “TXXXn” keywords like TTYPEn) will be overridden by the supplied column definitions, but all other informational and data model-specific keywords are kept.

nrowspython:int

Number of rows in the new table. If the input columns have data associated with them, the size of the largest input column is used. Otherwise the default is 0.

fillbool

If True, will fill all cells with zeros or blanks. If False, copy the data from input, undefined cells will still be filled with zeros/blanks.

character_as_bytesbool

Whether to return bytes for string columns when accessed from the HDU. By default this is False and (unicode) strings are returned, but for large tables this may use up a lot of memory.

Notes

Any additional keyword arguments accepted by the HDU class’s __init__ may also be passed in as keyword arguments.

classmethod fromstring(data, checksum=False, ignore_missing_end=False, **kwargs)

Creates a new HDU object of the appropriate type from a string containing the HDU’s entire header and, optionally, its data.

Note: When creating a new HDU from a string without a backing file object, the data of that HDU may be read-only. It depends on whether the underlying string was an immutable Python str/bytes object, or some kind of read-write memory buffer such as a memoryview.

Parameters:

datapython:str, bytearray, memoryview, ndarray

A byte string containing the HDU’s header and data.

checksumbool, optional

Check the HDU’s checksum and/or datasum.

ignore_missing_endbool, optional

Ignore a missing end card in the header data. Note that without the end card the end of the header may be ambiguous and resulted in a corrupt HDU. In this case the assumption is that the first 2880 block that does not begin with valid FITS header data is the beginning of the data.

**kwargsoptional

May consist of additional keyword arguments specific to an HDU type–these correspond to keywords recognized by the constructors of different HDU classes such as PrimaryHDU, ImageHDU, or BinTableHDU. Any unrecognized keyword arguments are simply ignored.

classmethod load(datafile, cdfile=None, hfile=None, replace=False, header=None)

Create a table from the input ASCII files. The input is from up to three separate files, one containing column definitions, one containing header parameters, and one containing column data.

The column definition and header parameters files are not required. When absent the column definitions and/or header parameters are taken from the header object given in the header argument; otherwise sensible defaults are inferred (though this mode is not recommended).

Parameters:

datafilepython:path-like object or python:file-like object

Input data file containing the table data in ASCII format.

cdfilepython:path-like object or python:file-like object, optional

Input column definition file containing the names, formats, display formats, physical units, multidimensional array dimensions, undefined values, scale factors, and offsets associated with the columns in the table. If None, the column definitions are taken from the current values in this object.

hfilepython:path-like object or python:file-like object, optional

Input parameter definition file containing the header parameter definitions to be associated with the table. If None, the header parameter definitions are taken from the current values in this objects header.

replacebool, optional

When True, indicates that the entire header should be replaced with the contents of the ASCII file instead of just updating the current header.

headerHeader, optional

When the cdfile and hfile are missing, use this Header object in the creation of the new table and HDU. Otherwise this Header supersedes the keywords from hfile, which is only used to update values not present in this Header, unless replace=True in which this Header’s values are completely replaced with the values from hfile.

Notes

The primary use for the load method is to allow the input of ASCII data that was edited in a standard text editor of the table data and parameters. The dump method can be used to create the initial ASCII files.

• datafile: Each line of the data file represents one row of table data. The data is output one column at a time in column order. If a column contains an array, each element of the column array in the current row is output before moving on to the next column. Each row ends with a new line.

  Integer data is output right-justified in a 21-character field followed by a blank. Floating point data is output right justified using ‘g’ format in a 21-character field with 15 digits of precision, followed by a blank. String data that does not contain whitespace is output left-justified in a field whose width matches the width specified in the TFORM header parameter for the column, followed by a blank. When the string data contains whitespace characters, the string is enclosed in quotation marks (""). For the last data element in a row, the trailing blank in the field is replaced by a new line character.

  For column data containing variable length arrays (‘P’ format), the array data is preceded by the string 'VLA_Length= ' and the integer length of the array for that row, left-justified in a 21-character field, followed by a blank.

  Note

  This format does not support variable length arrays using the (‘Q’ format) due to difficult to overcome ambiguities. What this means is that this file format cannot support VLA columns in tables stored in files that are over 2 GB in size.

  For column data representing a bit field (‘X’ format), each bit value in the field is output right-justified in a 21-character field as 1 (for true) or 0 (for false).

• cdfile: Each line of the column definitions file provides the definitions for one column in the table. The line is broken up into 8, sixteen-character fields. The first field provides the column name (TTYPEn). The second field provides the column format (TFORMn). The third field provides the display format (TDISPn). The fourth field provides the physical units (TUNITn). The fifth field provides the dimensions for a multidimensional array (TDIMn). The sixth field provides the value that signifies an undefined value (TNULLn). The seventh field provides the scale factor (TSCALn). The eighth field provides the offset value (TZEROn). A field value of "" is used to represent the case where no value is provided.

• hfile: Each line of the header parameters file provides the definition of a single HDU header card as represented by the card image.

classmethod match_header(header)

This is an abstract type that implements the shared functionality of the ASCII and Binary Table HDU types, which should be used instead of this.

classmethod readfrom(fileobj, checksum=False, ignore_missing_end=False, **kwargs)

Read the HDU from a file. Normally an HDU should be opened with open() which reads the entire HDU list in a FITS file. But this method is still provided for symmetry with writeto().

Parameters:

fileobjpython:file-like object

Input FITS file. The file’s seek pointer is assumed to be at the beginning of the HDU.

checksumbool

If True, verifies that both DATASUM and CHECKSUM card values (when present in the HDU header) match the header and data of all HDU’s in the file.

ignore_missing_endbool

Do not issue an exception when opening a file that is missing an END card in the last header.

req_cards(keyword, pos, test, fix_value, option, errlist)

Check the existence, location, and value of a required Card.

Parameters:

keywordpython:str

The keyword to validate

pospython:int, python:callable()

If an int, this specifies the exact location this card should have in the header. Remember that Python is zero-indexed, so this means pos=0 requires the card to be the first card in the header. If given a callable, it should take one argument–the actual position of the keyword–and return True or False. This can be used for custom evaluation. For example if pos=lambda idx: idx > 10 this will check that the keyword’s index is greater than 10.

testpython:callable()

This should be a callable (generally a function) that is passed the value of the given keyword and returns True or False. This can be used to validate the value associated with the given keyword.

fix_valuepython:str, python:int, python:float, complex, bool, python:None

A valid value for a FITS keyword to to use if the given test fails to replace an invalid value. In other words, this provides a default value to use as a replacement if the keyword’s current value is invalid. If None, there is no replacement value and the keyword is unfixable.

optionpython:str

Output verification option. Must be one of "fix", "silentfix", "ignore", "warn", or "exception". May also be any combination of "fix" or "silentfix" with "+ignore", +warn, or +exception" (e.g. ``"fix+warn"). See Verification Options for more info.

errlistpython:list

A list of validation errors already found in the FITS file; this is used primarily for the validation system to collect errors across multiple HDUs and multiple calls to req_cards.

Notes

If pos=None, the card can be anywhere in the header. If the card does not exist, the new card will have the fix_value as its value when created. Also check the card’s value by using the test argument.

run_option(option='warn', err_text='', fix_text='Fixed.', fix=None, fixable=True)

Execute the verification with selected option.

property size

Size (in bytes) of the data portion of the HDU.

update()

Update header keywords to reflect recent changes of columns.

verify(option='warn')

Verify all values in the instance.

Parameters:

optionpython:str

Output verification option. Must be one of "fix", "silentfix", "ignore", "warn", or "exception". May also be any combination of "fix" or "silentfix" with "+ignore", "+warn", or "+exception" (e.g. "fix+warn"). See Verification Options for more info.

verify_checksum()

Verify that the value in the CHECKSUM keyword matches the value calculated for the current HDU CHECKSUM.

Returns:

validpython:int

• 0 - failure

• 1 - success

• 2 - no CHECKSUM keyword present

verify_datasum()

Verify that the value in the DATASUM keyword matches the value calculated for the DATASUM of the current HDU data.

Returns:

validpython:int

• 0 - failure

• 1 - success

• 2 - no DATASUM keyword present

writeto(name, output_verify='exception', overwrite=False, checksum=False)

Works similarly to the normal writeto(), but prepends a default PrimaryHDU are required by extension HDUs (which cannot stand on their own).

TableHDU

class astropy.io.fits.TableHDU(data=None, header=None, name=None, ver=None, character_as_bytes=False)

Bases: _TableBaseHDU

FITS ASCII table extension HDU class.

Parameters:

dataarray or FITS_rec

Data to be used.

headerHeader

Header to be used.

namepython:str

Name to be populated in EXTNAME keyword.

verpython:int > 0 or python:None, optional

The ver of the HDU, will be the value of the keyword EXTVER. If not given or None, it defaults to the value of the EXTVER card of the header or 1. (default: None)

character_as_bytesbool

Whether to return bytes for string columns. By default this is False and (unicode) strings are returned, but this does not respect memory mapping and loads the whole column in memory when accessed.

add_checksum(when=None, override_datasum=False, checksum_keyword='CHECKSUM', datasum_keyword='DATASUM')

Add the CHECKSUM and DATASUM cards to this HDU with the values set to the checksum calculated for the HDU and the data respectively. The addition of the DATASUM card may be overridden.

Parameters:

whenpython:str, optional

comment string for the cards; by default the comments will represent the time when the checksum was calculated

override_datasumbool, optional

add the CHECKSUM card only

checksum_keywordpython:str, optional

The name of the header keyword to store the checksum value in; this is typically ‘CHECKSUM’ per convention, but there exist use cases in which a different keyword should be used

datasum_keywordpython:str, optional

See checksum_keyword

Notes

For testing purposes, first call add_datasum with a when argument, then call add_checksum with a when argument and override_datasum set to True. This will provide consistent comments for both cards and enable the generation of a CHECKSUM card with a consistent value.

add_datasum(when=None, datasum_keyword='DATASUM')

Add the DATASUM card to this HDU with the value set to the checksum calculated for the data.

Parameters:

whenpython:str, optional

Comment string for the card that by default represents the time when the checksum was calculated

datasum_keywordpython:str, optional

The name of the header keyword to store the datasum value in; this is typically ‘DATASUM’ per convention, but there exist use cases in which a different keyword should be used

Returns:

checksumpython:int

The calculated datasum

Notes

For testing purposes, provide a when argument to enable the comment value in the card to remain consistent. This will enable the generation of a CHECKSUM card with a consistent value.

property columns

The ColDefs objects describing the columns in this table.

copy()

Make a copy of the table HDU, both header and data are copied.

filebytes()

Calculates and returns the number of bytes that this HDU will write to a file.

fileinfo()

Returns a dictionary detailing information about the locations of this HDU within any associated file. The values are only valid after a read or write of the associated file with no intervening changes to the HDUList.

Returns:

python:dict or python:None

The dictionary details information about the locations of this HDU within an associated file. Returns None when the HDU is not associated with a file.

Dictionary contents:

Key	Value
file	File object associated with the HDU
filemode	Mode in which the file was opened (readonly, copyonwrite, update, append, ostream)
hdrLoc	Starting byte location of header in file
datLoc	Starting byte location of data block in file
datSpan	Data size including padding

classmethod from_columns(columns, header=None, nrows=0, fill=False, character_as_bytes=False, **kwargs)

Given either a ColDefs object, a sequence of Column objects, or another table HDU or table data (a FITS_rec or multi-field numpy.ndarray or numpy.recarray object, return a new table HDU of the class this method was called on using the column definition from the input.

See also FITS_rec.from_columns.

Parameters:

columnspython:sequence of Column, ColDefs astropy:-like

The columns from which to create the table data, or an object with a column-like structure from which a ColDefs can be instantiated. This includes an existing BinTableHDU or TableHDU, or a numpy.recarray to give some examples.

If these columns have data arrays attached that data may be used in initializing the new table. Otherwise the input columns will be used as a template for a new table with the requested number of rows.

headerHeader

An optional Header object to instantiate the new HDU yet. Header keywords specifically related to defining the table structure (such as the “TXXXn” keywords like TTYPEn) will be overridden by the supplied column definitions, but all other informational and data model-specific keywords are kept.

nrowspython:int

Number of rows in the new table. If the input columns have data associated with them, the size of the largest input column is used. Otherwise the default is 0.

fillbool

If True, will fill all cells with zeros or blanks. If False, copy the data from input, undefined cells will still be filled with zeros/blanks.

character_as_bytesbool

Whether to return bytes for string columns when accessed from the HDU. By default this is False and (unicode) strings are returned, but for large tables this may use up a lot of memory.

Notes

Any additional keyword arguments accepted by the HDU class’s __init__ may also be passed in as keyword arguments.

classmethod fromstring(data, checksum=False, ignore_missing_end=False, **kwargs)

Creates a new HDU object of the appropriate type from a string containing the HDU’s entire header and, optionally, its data.

Note: When creating a new HDU from a string without a backing file object, the data of that HDU may be read-only. It depends on whether the underlying string was an immutable Python str/bytes object, or some kind of read-write memory buffer such as a memoryview.

Parameters:

datapython:str, bytearray, memoryview, ndarray

A byte string containing the HDU’s header and data.

checksumbool, optional

Check the HDU’s checksum and/or datasum.

ignore_missing_endbool, optional

Ignore a missing end card in the header data. Note that without the end card the end of the header may be ambiguous and resulted in a corrupt HDU. In this case the assumption is that the first 2880 block that does not begin with valid FITS header data is the beginning of the data.

**kwargsoptional

May consist of additional keyword arguments specific to an HDU type–these correspond to keywords recognized by the constructors of different HDU classes such as PrimaryHDU, ImageHDU, or BinTableHDU. Any unrecognized keyword arguments are simply ignored.

classmethod match_header(header)

This is an abstract type that implements the shared functionality of the ASCII and Binary Table HDU types, which should be used instead of this.

classmethod readfrom(fileobj, checksum=False, ignore_missing_end=False, **kwargs)

Read the HDU from a file. Normally an HDU should be opened with open() which reads the entire HDU list in a FITS file. But this method is still provided for symmetry with writeto().

Parameters:

fileobjpython:file-like object

Input FITS file. The file’s seek pointer is assumed to be at the beginning of the HDU.

checksumbool

If True, verifies that both DATASUM and CHECKSUM card values (when present in the HDU header) match the header and data of all HDU’s in the file.

ignore_missing_endbool

Do not issue an exception when opening a file that is missing an END card in the last header.

req_cards(keyword, pos, test, fix_value, option, errlist)

Check the existence, location, and value of a required Card.

Parameters:

keywordpython:str

The keyword to validate

pospython:int, python:callable()

If an int, this specifies the exact location this card should have in the header. Remember that Python is zero-indexed, so this means pos=0 requires the card to be the first card in the header. If given a callable, it should take one argument–the actual position of the keyword–and return True or False. This can be used for custom evaluation. For example if pos=lambda idx: idx > 10 this will check that the keyword’s index is greater than 10.

testpython:callable()

This should be a callable (generally a function) that is passed the value of the given keyword and returns True or False. This can be used to validate the value associated with the given keyword.

fix_valuepython:str, python:int, python:float, complex, bool, python:None

A valid value for a FITS keyword to to use if the given test fails to replace an invalid value. In other words, this provides a default value to use as a replacement if the keyword’s current value is invalid. If None, there is no replacement value and the keyword is unfixable.

optionpython:str

Output verification option. Must be one of "fix", "silentfix", "ignore", "warn", or "exception". May also be any combination of "fix" or "silentfix" with "+ignore", +warn, or +exception" (e.g. ``"fix+warn"). See Verification Options for more info.

errlistpython:list

A list of validation errors already found in the FITS file; this is used primarily for the validation system to collect errors across multiple HDUs and multiple calls to req_cards.

Notes

If pos=None, the card can be anywhere in the header. If the card does not exist, the new card will have the fix_value as its value when created. Also check the card’s value by using the test argument.

run_option(option='warn', err_text='', fix_text='Fixed.', fix=None, fixable=True)

Execute the verification with selected option.

property size

Size (in bytes) of the data portion of the HDU.

update()

Update header keywords to reflect recent changes of columns.

verify(option='warn')

Verify all values in the instance.

Parameters:

optionpython:str

Output verification option. Must be one of "fix", "silentfix", "ignore", "warn", or "exception". May also be any combination of "fix" or "silentfix" with "+ignore", "+warn", or "+exception" (e.g. "fix+warn"). See Verification Options for more info.

verify_checksum()

Verify that the value in the CHECKSUM keyword matches the value calculated for the current HDU CHECKSUM.

Returns:

validpython:int

• 0 - failure

• 1 - success

• 2 - no CHECKSUM keyword present

verify_datasum()

Verify that the value in the DATASUM keyword matches the value calculated for the DATASUM of the current HDU data.

Returns:

validpython:int

• 0 - failure

• 1 - success

• 2 - no DATASUM keyword present

writeto(name, output_verify='exception', overwrite=False, checksum=False)

Works similarly to the normal writeto(), but prepends a default PrimaryHDU are required by extension HDUs (which cannot stand on their own).

Column

class astropy.io.fits.Column(name=None, format=None, unit=None, null=None, bscale=None, bzero=None, disp=None, start=None, dim=None, array=None, ascii=None, coord_type=None, coord_unit=None, coord_ref_point=None, coord_ref_value=None, coord_inc=None, time_ref_pos=None)

Bases: NotifierMixin

Class which contains the definition of one column, e.g. ttype, tform, etc. and the array containing values for the column.

Construct a Column by specifying attributes. All attributes except format can be optional; see Column Creation and Creating an ASCII Table for more information regarding TFORM keyword.

Parameters:

namepython:str, optional

column name, corresponding to TTYPE keyword

formatpython:str

column format, corresponding to TFORM keyword

unitpython:str, optional

column unit, corresponding to TUNIT keyword

nullpython:str, optional

null value, corresponding to TNULL keyword

bscaleint-like, optional

bscale value, corresponding to TSCAL keyword

bzeroint-like, optional

bzero value, corresponding to TZERO keyword

disppython:str, optional

display format, corresponding to TDISP keyword

startpython:int, optional

column starting position (ASCII table only), corresponding to TBCOL keyword

dimpython:str, optional

column dimension corresponding to TDIM keyword

arraypython:iterable, optional

a list, numpy.ndarray (or other iterable that can be used to initialize an ndarray) providing initial data for this column. The array will be automatically converted, if possible, to the data format of the column. In the case were non-trivial bscale and/or bzero arguments are given, the values in the array must be the physical values–that is, the values of column as if the scaling has already been applied (the array stored on the column object will then be converted back to its storage values).

asciibool, optional

set True if this describes a column for an ASCII table; this may be required to disambiguate the column format

coord_typepython:str, optional

coordinate/axis type corresponding to TCTYP keyword

coord_unitpython:str, optional

coordinate/axis unit corresponding to TCUNI keyword

coord_ref_pointint-like, optional

pixel coordinate of the reference point corresponding to TCRPX keyword

coord_ref_valueint-like, optional

coordinate value at reference point corresponding to TCRVL keyword

coord_incint-like, optional

coordinate increment at reference point corresponding to TCDLT keyword

time_ref_pospython:str, optional

reference position for a time coordinate column corresponding to TRPOS keyword

property array

The Numpy ndarray associated with this Column.

If the column was instantiated with an array passed to the array argument, this will return that array. However, if the column is later added to a table, such as via BinTableHDU.from_columns as is typically the case, this attribute will be updated to reference the associated field in the table, which may no longer be the same array.

property ascii

Whether this Column represents a column in an ASCII table.

copy()

Return a copy of this Column.

ColDefs

class astropy.io.fits.ColDefs(input, ascii=False)

Bases: NotifierMixin

Column definitions class.

It has attributes corresponding to the Column attributes (e.g. ColDefs has the attribute names while Column has name). Each attribute in ColDefs is a list of corresponding attribute values from all Column objects.

Parameters:

inputpython:sequence of Column or ColDefs or ndarray or recarray

An existing table HDU, an existing ColDefs, or any multi-field Numpy array or numpy.recarray.

asciibool

Use True to ensure that ASCII table columns are used.

add_col(column)

Append one Column to the column definition.

change_attrib(col_name, attrib, new_value)

Change an attribute (in the KEYWORD_ATTRIBUTES list) of a Column.

Parameters:

col_namepython:str or python:int

The column name or index to change

attribpython:str

The attribute name

new_valueobject

The new value for the attribute

change_name(col_name, new_name)

Change a Column’s name.

Parameters:

col_namepython:str

The current name of the column

new_namepython:str

The new name of the column

change_unit(col_name, new_unit)

Change a Column’s unit.

Parameters:

col_namepython:str or python:int

The column name or index

new_unitpython:str

The new unit for the column

del_col(col_name)

Delete (the definition of) one Column.

col_namestr or int

The column’s name or index

info(attrib='all', output=None)

Get attribute(s) information of the column definition.

Parameters:

attribpython:str

Can be one or more of the attributes listed in astropy.io.fits.column.KEYWORD_ATTRIBUTES. The default is "all" which will print out all attributes. It forgives plurals and blanks. If there are two or more attribute names, they must be separated by comma(s).

outputpython:file-like object, optional

File-like object to output to. Outputs to stdout by default. If False, returns the attributes as a dict instead.

Notes

This function doesn’t return anything by default; it just prints to stdout.

FITS_rec

class astropy.io.fits.FITS_rec(input)

Bases: recarray

FITS record array class.

FITS_rec is the data part of a table HDU’s data part. This is a layer over the recarray, so we can deal with scaled columns.

It inherits all of the standard methods from numpy.ndarray.

Construct a FITS record array from a recarray.

property columns

A user-visible accessor for the coldefs.

copy(order='C')

The Numpy documentation lies; numpy.ndarray.copy is not equivalent to numpy.copy. Differences include that it re-views the copied array as self’s ndarray subclass, as though it were taking a slice; this means __array_finalize__ is called and the copy shares all the array attributes (including ._converted!). So we need to make a deep copy of all those attributes so that the two arrays truly do not share any data.

field(key)

A view of a Column’s data as an array.

property formats

List of column FITS formats.

classmethod from_columns(columns, nrows=0, fill=False, character_as_bytes=False)

Given a ColDefs object of unknown origin, initialize a new FITS_rec object.

Note

This was originally part of the new_table function in the table module but was moved into a class method since most of its functionality always had more to do with initializing a FITS_rec object than anything else, and much of it also overlapped with FITS_rec._scale_back.

Parameters:

columnspython:sequence of Column or a ColDefs

The columns from which to create the table data. If these columns have data arrays attached that data may be used in initializing the new table. Otherwise the input columns will be used as a template for a new table with the requested number of rows.

nrowspython:int

Number of rows in the new table. If the input columns have data associated with them, the size of the largest input column is used. Otherwise the default is 0.

fillbool

If True, will fill all cells with zeros or blanks. If False, copy the data from input, undefined cells will still be filled with zeros/blanks.

property names

List of column names.

tolist()

Return the array as an a.ndim-levels deep nested list of Python scalars.

Return a copy of the array data as a (nested) Python list. Data items are converted to the nearest compatible builtin Python type, via the item function.

If a.ndim is 0, then since the depth of the nested list is 0, it will not be a list at all, but a simple Python scalar.

Parameters:

none

Returns:

yobject, or python:list of object, or python:list of python:list of object, or …

The possibly nested list of array elements.

Notes

The array may be recreated via a = np.array(a.tolist()), although this may sometimes lose precision.

Examples

For a 1D array, a.tolist() is almost the same as list(a), except that tolist changes numpy scalars to Python scalars:

>>> a = np.uint32([1, 2])
>>> a_list = list(a)
>>> a_list
[1, 2]
>>> type(a_list[0])
<class 'numpy.uint32'>
>>> a_tolist = a.tolist()
>>> a_tolist
[1, 2]
>>> type(a_tolist[0])
<class 'int'>

Additionally, for a 2D array, tolist applies recursively:

>>> a = np.array([[1, 2], [3, 4]])
>>> list(a)
[array([1, 2]), array([3, 4])]
>>> a.tolist()
[[1, 2], [3, 4]]

The base case for this recursion is a 0D array:

>>> a = np.array(1)
>>> list(a)
Traceback (most recent call last):
  ...
TypeError: iteration over a 0-d array
>>> a.tolist()
1

FITS_record

class astropy.io.fits.FITS_record(input, row=0, start=None, end=None, step=None, base=None, **kwargs)

Bases: object

FITS record class.

FITS_record is used to access records of the FITS_rec object. This will allow us to deal with scaled columns. It also handles conversion/scaling of columns in ASCII tables. The FITS_record class expects a FITS_rec object as input.

Parameters:

inputarray

The array to wrap.

rowpython:int, optional

The starting logical row of the array.

startpython:int, optional

The starting column in the row associated with this object. Used for subsetting the columns of the FITS_rec object.

endpython:int, optional

The ending column in the row associated with this object. Used for subsetting the columns of the FITS_rec object.

field(field)

Get the field data of the record.

setfield(field, value)

Set the field data of the record.

Table Functions

tabledump()

astropy.io.fits.tabledump(filename, datafile=None, cdfile=None, hfile=None, ext=1, overwrite=False)

Dump a table HDU to a file in ASCII format. The table may be dumped in three separate files, one containing column definitions, one containing header parameters, and one for table data.

Parameters:

filenamepython:path-like object or python:file-like object

Input fits file.

datafilepython:path-like object or python:file-like object, optional

Output data file. The default is the root name of the input fits file appended with an underscore, followed by the extension number (ext), followed by the extension .txt.

cdfilepython:path-like object or python:file-like object, optional

Output column definitions file. The default is None, no column definitions output is produced.

hfilepython:path-like object or python:file-like object, optional

Output header parameters file. The default is None, no header parameters output is produced.

extpython:int

The number of the extension containing the table HDU to be dumped.

overwritebool, optional

If True, overwrite the output file if it exists. Raises an OSError if False and the output file exists. Default is False.

Notes

The primary use for the tabledump function is to allow editing in a standard text editor of the table data and parameters. The tableload function can be used to reassemble the table from the three ASCII files.

• datafile: Each line of the data file represents one row of table data. The data is output one column at a time in column order. If a column contains an array, each element of the column array in the current row is output before moving on to the next column. Each row ends with a new line.

  Integer data is output right-justified in a 21-character field followed by a blank. Floating point data is output right justified using ‘g’ format in a 21-character field with 15 digits of precision, followed by a blank. String data that does not contain whitespace is output left-justified in a field whose width matches the width specified in the TFORM header parameter for the column, followed by a blank. When the string data contains whitespace characters, the string is enclosed in quotation marks (""). For the last data element in a row, the trailing blank in the field is replaced by a new line character.

  For column data containing variable length arrays (‘P’ format), the array data is preceded by the string 'VLA_Length= ' and the integer length of the array for that row, left-justified in a 21-character field, followed by a blank.

  Note

  This format does not support variable length arrays using the (‘Q’ format) due to difficult to overcome ambiguities. What this means is that this file format cannot support VLA columns in tables stored in files that are over 2 GB in size.

  For column data representing a bit field (‘X’ format), each bit value in the field is output right-justified in a 21-character field as 1 (for true) or 0 (for false).

• cdfile: Each line of the column definitions file provides the definitions for one column in the table. The line is broken up into 8, sixteen-character fields. The first field provides the column name (TTYPEn). The second field provides the column format (TFORMn). The third field provides the display format (TDISPn). The fourth field provides the physical units (TUNITn). The fifth field provides the dimensions for a multidimensional array (TDIMn). The sixth field provides the value that signifies an undefined value (TNULLn). The seventh field provides the scale factor (TSCALn). The eighth field provides the offset value (TZEROn). A field value of "" is used to represent the case where no value is provided.

• hfile: Each line of the header parameters file provides the definition of a single HDU header card as represented by the card image.

tableload()

astropy.io.fits.tableload(datafile, cdfile, hfile=None)

Create a table from the input ASCII files. The input is from up to three separate files, one containing column definitions, one containing header parameters, and one containing column data. The header parameters file is not required. When the header parameters file is absent a minimal header is constructed.

Parameters:

datafilepython:path-like object or python:file-like object

Input data file containing the table data in ASCII format.

cdfilepython:path-like object or python:file-like object

Input column definition file containing the names, formats, display formats, physical units, multidimensional array dimensions, undefined values, scale factors, and offsets associated with the columns in the table.

hfilepython:path-like object or python:file-like object, optional

Input parameter definition file containing the header parameter definitions to be associated with the table. If None, a minimal header is constructed.

Notes

The primary use for the tableload function is to allow the input of ASCII data that was edited in a standard text editor of the table data and parameters. The tabledump function can be used to create the initial ASCII files.

• datafile: Each line of the data file represents one row of table data. The data is output one column at a time in column order. If a column contains an array, each element of the column array in the current row is output before moving on to the next column. Each row ends with a new line.

  Integer data is output right-justified in a 21-character field followed by a blank. Floating point data is output right justified using ‘g’ format in a 21-character field with 15 digits of precision, followed by a blank. String data that does not contain whitespace is output left-justified in a field whose width matches the width specified in the TFORM header parameter for the column, followed by a blank. When the string data contains whitespace characters, the string is enclosed in quotation marks (""). For the last data element in a row, the trailing blank in the field is replaced by a new line character.

  For column data containing variable length arrays (‘P’ format), the array data is preceded by the string 'VLA_Length= ' and the integer length of the array for that row, left-justified in a 21-character field, followed by a blank.

  Note

  This format does not support variable length arrays using the (‘Q’ format) due to difficult to overcome ambiguities. What this means is that this file format cannot support VLA columns in tables stored in files that are over 2 GB in size.

  For column data representing a bit field (‘X’ format), each bit value in the field is output right-justified in a 21-character field as 1 (for true) or 0 (for false).

• cdfile: Each line of the column definitions file provides the definitions for one column in the table. The line is broken up into 8, sixteen-character fields. The first field provides the column name (TTYPEn). The second field provides the column format (TFORMn). The third field provides the display format (TDISPn). The fourth field provides the physical units (TUNITn). The fifth field provides the dimensions for a multidimensional array (TDIMn). The sixth field provides the value that signifies an undefined value (TNULLn). The seventh field provides the scale factor (TSCALn). The eighth field provides the offset value (TZEROn). A field value of "" is used to represent the case where no value is provided.

• hfile: Each line of the header parameters file provides the definition of a single HDU header card as represented by the card image.

table_to_hdu()

astropy.io.fits.table_to_hdu(table, character_as_bytes=False)

Convert an Table object to a FITS BinTableHDU.

Parameters:

tableastropy.table.Table

The table to convert.

character_as_bytesbool

Whether to return bytes for string columns when accessed from the HDU. By default this is False and (unicode) strings are returned, but for large tables this may use up a lot of memory.

Returns:

table_hduBinTableHDU

The FITS binary table HDU.